CloudPhysics vs. Control Plane Comparison Chart

Compute Engine is Google's infrastructure as a service (IaaS) platform for organizations to create and run cloud-based virtual machines. Computing infrastructure in predefined or custom machine sizes to accelerate your cloud transformation. General purpose (E2, N1, N2, N2D) machines provide a good balance of price and performance. Compute optimized (C2) machines offer high-end vCPU performance for compute-intensive workloads. Memory optimized (M2) machines offer the highest memory and are great for in-memory databases. Accelerator optimized (A2) machines are based on the A100 GPU, for very demanding applications. Integrate Compute with other Google Cloud services such as AI/ML and data analytics. Make reservations to help ensure your applications have the capacity they need as they scale. Save money just for running Compute with sustained-use discounts, and achieve greater savings when you use committed-use discounts.

IONOS GPU Servers provide an accelerated computing infrastructure designed to handle workloads that require significantly more processing power than traditional CPU-based systems. It integrates enterprise-grade NVIDIA GPUs such as the H100, H200, and L40s, as well as specialized AI accelerators like Intel Gaudi, enabling massive parallel processing for compute-intensive applications. GPU-accelerated instances extend cloud infrastructure with dedicated graphics processors so virtual machines can perform complex calculations and data-heavy operations much faster than conventional servers. It is particularly suitable for artificial intelligence, deep learning, and data science tasks that involve training models on large datasets or performing high-speed inference operations. It also supports big data analytics, scientific simulations, and visualization workloads such as 3D rendering or modeling that require high computational throughput.

Runpod offers a cloud-based platform designed for running AI workloads, focusing on providing scalable, on-demand GPU resources to accelerate machine learning (ML) model training and inference. With its diverse selection of powerful GPUs like the NVIDIA A100, RTX 3090, and H100, Runpod supports a wide range of AI applications, from deep learning to data processing. The platform is designed to minimize startup time, providing near-instant access to GPU pods, and ensures scalability with autoscaling capabilities for real-time AI model deployment. Runpod also offers serverless functionality, job queuing, and real-time analytics, making it an ideal solution for businesses needing flexible, cost-effective GPU resources without the hassle of managing infrastructure.

Servers.com by Nexcess provides hybrid bare metal cloud infrastructure designed to help businesses scale, customize, and manage their server environments from a unified platform. The company offers a range of solutions including Scalable Bare Metal, Enterprise Bare Metal, AI Compute, and Managed Kubernetes to support diverse workload requirements. Its global network of strategically located data centers helps organizations reduce latency and improve performance for users around the world. Servers.com serves industries such as gaming, fintech, adtech, streaming, SaaS, iGaming, and Web3, delivering reliable infrastructure tailored to each sector's needs. The platform combines dedicated bare metal resources with flexible deployment options to help businesses balance performance, scalability, and cost. With high-performance networking, resource isolation, and global connectivity, Servers.com enables organizations to support mission-critical applications and demanding workloads.

Dragonfly is a drop-in Redis replacement that cuts costs and boosts performance. Designed to fully utilize the power of modern cloud hardware and deliver on the data demands of modern applications, Dragonfly frees developers from the limits of traditional in-memory data stores. The power of modern cloud hardware can never be realized with legacy software. Dragonfly is optimized for modern cloud computing, delivering 25x more throughput and 12x lower snapshotting latency when compared to legacy in-memory data stores like Redis, making it easy to deliver the real-time experience your customers expect. Scaling Redis workloads is expensive due to their inefficient, single-threaded model. Dragonfly is far more compute and memory efficient, resulting in up to 80% lower infrastructure costs. Dragonfly scales vertically first, only requiring clustering at an extremely high scale. This results in a far simpler operational model and a more reliable system.

Bacula Enterprise delivers backup and recovery for demanding enterprise, high-performance computing (HPC), defense, government and research environments. Developed by Switzerland-based Bacula Systems, it protects physical, virtual, container, database, SaaS and cloud workloads through one centrally managed platform. Keep backup data and recovery operations under your control. Bacula supports fully on-premises deployment without mandatory cloud control planes, call-home licensing or continuous internet connectivity. Organizations can retain control over storage location, infrastructure, encryption keys and recovery procedures to support data sovereignty and operational independence. Build layered ransomware resilience with physically air-gapped tape and offline copies, immutable storage options, encryption, multi-factor authentication, granular access controls and file integrity verification. Security capabilities can be configured around defense, critical infrastructure and other sensitive environments. For petabyte-scale HPC and research datasets, Bacula offers HPC Accelerator, parallel backup processing and integrations with Lustre, GPFS and ZFS. Protect large file populations while combining disk, tape libraries, object storage and cloud targets. Licensing is not based on protected data volume. Virtualization and cloud VM coverage includes VMware vSphere/ESXi, Hyper-V, Proxmox, Nutanix AHV, XenServer, XCP-ng, KVM, QEMU, Libvirt, Red Hat Virtualization, OpenStack, Amazon EC2 and Azure VMs. Container protection covers Kubernetes, Red Hat OpenShift and Docker. Database protection includes Oracle, SQL Server, PostgreSQL, MySQL, Percona for MySQL, MariaDB, SAP HANA, Sybase ASE, IBM Db2, MongoDB, Hadoop HDFS and InterSystems IRIS, plus Amazon RDS integration. Additional workloads include Microsoft 365 and Google Workspace. Automated scheduling, monitoring, reporting, deduplication, compression and BWeb web-based administration help teams manage distributed infrastructure. Recovery options include files, application data, virtual machines and bare metal recovery for supported systems. Built on an open-source core, Bacula Enterprise combines open source foundation with enterprise-only plugins, security capabilities, management tools and commercial support. This open core approach provides transparency while extending the platform for complex, large-scale and security-sensitive environments.

FinOpsly is an AI Cost Governance platform. It brings AI, cloud, data platform and SaaS spend into one attribution, policy and control layer, so enterprises can price a workload before building it, attribute every dollar to an owner, hold spend inside budget under policy, and prove what landed in run-rate. Your AI invoice is not what your AI costs. One request draws on model tokens, retrieval, warehouse queries, GPU capacity and storage, and only the first shows up on the AI bill. FinOpsly resolves all of it, plus the seats in procurement and the compute in an untagged cloud account, to the same dimensions: owner, team, application, line of business, customer and tenant. An AI initiative's full cost becomes one figure, charged back through one hierarchy in one cycle. Workforce AI is the tools employees use: seats and per-user token draw across GitHub Copilot, Cursor, ChatGPT Enterprise and Microsoft 365 Copilot. Application AI is the AI your product ships: tokens, compute and data joined into cost-to-serve across OpenAI, Anthropic, Bedrock, Azure OpenAI, Vertex AI, SageMaker and Databricks. PLAN. Price a workload from its architecture before any resource exists, across model APIs, GPU capacity, data platform consumption and storage, with assumptions visible. Compare it across candidate models on your measured usage. EXPLAIN. Attribute spend to owner, team, application, line of business and business unit across 9+ hierarchy levels. Unified tagging reconciles providers that tag inconsistently, and AI-driven bulk labeling closes large key estates. Unattributed spend is reported in dollars. ACT. Budgets per project, team and API key, with daily burn-rate monitoring. Anomaly detection with root cause, routed to the owner. Waste detection using FinOpsly's own algorithms and ML models. Commitment planning across AWS, Azure and Google Cloud. Policy-driven parking of idle compute. PROVE. Chargeback across AI, cloud, data and SaaS in one cycle. Realized savings tracked into run-rate against a no-action baseline. Cost per call, cost per active user, and cost-to-serve per customer and tenant. proof: 100% attribution of AI spend; chargeback from 12.4 days to under one day across 9+ levels; 26% realized savings in AWS and 17%+ in Azure at a payments client. Built for CIOs, CTOs and platform leaders accountable for technology spend, FinOps and finance teams running chargeback, and engineering teams who need cost signal before they decide

Veeam Data Platform is a unified data resilience solution that helps organizations recover from cyberattacks and outages, and protect workloads across hybrid and multicloud environments – all without vendor lock-in. The platform includes built-in security capabilities designed to mitigate ransomware and other data-loss threats, including AI-backed threat detection across a broad range of workload types. This is intended to help teams identify and respond to threats before they disrupt operations. Veeam Data Platform supports workload portability across hypervisors, cloud providers, and on-premises environments, allowing organizations to move or recover data across infrastructure without being tied to a specific vendor or platform. For organizations looking to simplify deployment, Veeam Software Appliance provides a pre-built, hardened, and highly available option, reducing the manual setup and maintenance work required from IT teams. Veeam Data Platform is used by over 550,000 customers worldwide, including 82% of the Fortune 500.

Kasm Workspaces streams your workplace environment directly to your web browser…on any device and from any location. Kasm uses our high-performance streaming and secure isolation technology to provide web-native Desktop as a Service (DaaS), application streaming, and secure/private web browsing. Kasm is not just a service; it is a highly configurable platform with a robust developer API and devops-enabled workflows that can be customized for your use-case, at any scale. Workspaces can be deployed in the cloud (Public or Private), on-premise (Including Air-Gapped Networks or your Homelab), or in a hybrid configuration.

Google Cloud is a cloud-based service that allows you to create anything from simple websites to complex applications for businesses of all sizes. New customers get $300 in free credits to run, test, and deploy workloads. All customers can use 25+ products for free, up to monthly usage limits. Use Google's core infrastructure, data analytics & machine learning. Secure and fully featured for all enterprises. Tap into big data to find answers faster and build better products. Grow from prototype to production to planet-scale, without having to think about capacity, reliability or performance. From virtual machines with proven price/performance advantages to a fully managed app development platform. Scalable, resilient, high performance object storage and databases for your applications. State-of-the-art software-defined networking products on Google’s private fiber network. Fully managed data warehousing, batch and stream processing, data exploration, Hadoop/Spark, and messaging.